Network architecture.
The network consists of three convolutional blocks, composed of convolution, relu, average pooling and Group Normalization (GN) layers, followed by fully-connected and sigmoid layers. GN is used instead of batch-normalization (BN) following the observations that BN does not work well in non-iid data setting similar to our case [1]}. Table (REF ) provides the details of the network architecture.
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